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Título: | Parallel photonic information processing at gigabyte per second data rates using transient states |
Autor: | Brunner, Daniel CSIC ORCID; Soriano, Miguel C. ; Mirasso, Claudio R. CSIC ORCID ; Fischer, Ingo CSIC ORCID | Fecha de publicación: | 15-ene-2013 | Editor: | Nature Publishing Group | Citación: | Nature Communications 4: 1364 (2013) | Resumen: | The increasing demands on information processing require novel computational concepts and true parallelism. Nevertheless, hardware realizations of unconventional computing approaches never exceeded a marginal existence. While the application of optics in super-computing receives reawakened interest, new concepts, partly neuro-inspired, are being considered and developed. Here we experimentally demonstrate the potential of a simple photonic architecture to process information at unprecedented data rates, implementing a learning-based approach. A semiconductor laser subject to delayed self-feedback and optical data injection is employed to solve computationally hard tasks. We demonstrate simultaneous spoken digit and speaker recognition and chaotic time-series prediction at data rates beyond 1 Gbyte/s. We identify all digits with very low classification errors and perform chaotic time-series prediction with 10% error. Our approach bridges the areas of photonic information processing, cognitive and information science. © 2013 Macmillan Publishers Limited. All rights reserved. | Versión del editor: | http://dx.doi.org/10.1038/ncomms2368 | URI: | http://hdl.handle.net/10261/117138 | DOI: | 10.1038/ncomms2368 | Identificadores: | doi: 10.1038/ncomms2368 issn: 2041-1723 |
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parallel_photonic_information_Brunner.pdf | 1,27 MB | Adobe PDF | Visualizar/Abrir |
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